Top AI Engineer Jobs

The role involves designing and developing machine learning infrastructure and models, consulting on best practices, and building scalable services for AI integration.

As a Senior Machine Learning Engineer, you will design ML infrastructure, build AI features, and collaborate with cross-functional teams while managing large data sets.

This role involves leading research and technology development in AI/ML for semiconductor equipment, focusing on autonomous operation, software/hardware systems, and knowledge management.

The Senior Software Engineer will develop AI/ML systems for debugging in production environments, integrating predictive analytics and issue resolution tools.

The AI/ML Engineer will identify and scale generative AI technologies, lead pilot projects, collaborate on implementations, and refine AI outputs.

As an AI Software Engineer, you will integrate AI tools into workflows, optimize performance, and coordinate AI agents to improve design productivity within the organization.

The Sr. AI/LLM Infrastructure SW Engineer will develop AI models, lead architectural evaluations, and define AIOS solutions in vehicles, necessitating teamwork and strategic planning.

Responsible for architecting AIOS solutions, leading proof-of-concepts, collaborating with engineering teams, defining roadmaps, and delivering project requirements.

The IT AI Innovation Engineer will design and maintain AI-driven software systems, build workflows, collaborate across teams, and ensure security in development practices.

As an AI/ML Engineer, you'll design, build, and ship large scale NLP and LLM systems for classification, ranking, and content generation while collaborating with cross-functional teams.

As an AI Data Engineer, you will transform unstructured datasets, build ETL workflows, ensure data quality, and collaborate with teams to enhance AI decisions.

Build and scale the infrastructure for AI services, focusing on Kubernetes, Elastic Stack, and cloud technologies. Collaborate with teams to optimize platform performance and security.

The Agentic AI Engineer will design and develop AI-driven workflows, supporting enterprise clients in automating processes, and ensuring secure implementations that deliver measurable ROI.

As an AI Software Engineer, develop and maintain an AI platform, troubleshoot issues, build integrations, and participate in the software lifecycle.

The AI Solutions Engineer will design, implement, and deploy AI solutions for US Government customers, focusing on generative and predictive capabilities while interacting with stakeholders to create prototypes and innovative solutions.

The Senior Engineer 2 in Applied AI builds and deploys solutions supporting business workflows, ensuring compliance and security in a regulated environment, collaborating with teams to enhance AI applications and processes.

Build and optimize backend systems for AI-powered features, focusing on monitoring, reliability, latency, and inference processes.

The role involves scaling and optimizing a Generative AI product by designing APIs, enhancing infrastructure, and collaborating with cross-functional teams. Responsibilities include implementing metrics and tracing frameworks to monitor performance and usability while fostering coding best practices.

Design and build production-grade AI systems, translating real-world problems into scalable AI-driven solutions while mentoring engineers and shaping technical strategy.

The Software Engineer, AI will develop intelligent systems for financial workflows, utilizing LLMs and other technologies to enhance bookkeeping and data processing for agriculture businesses.

The Research Engineer will develop the DeOS framework, optimizing AI workloads, managing GPU resources, ensuring scalability, and contributing to open-source projects.

The AI Software Engineer will design and implement AI-powered features, focusing on machine learning models and their integration into production systems. Responsibilities include end-to-end development, experimentation with new tools, and improving software performance.

Develop full-stack solutions for a robot management portal, including user authentication and data management, leveraging cloud-based technologies.

Develop Python-based ML components for spatial data quality, design robust software, and collaborate in an Agile environment.

Develop and maintain backend applications with Python, integrate Generative AI models, work in Agile teams, and ensure code quality.